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  <div class="section" id="module-pyvib.linalg">
<span id="linear-algebra"></span><h1>Linear algebra<a class="headerlink" href="#module-pyvib.linalg" title="Permalink to this headline">¶</a></h1>
<p>linalg</p>
<dl class="function">
<dt id="pyvib.linalg.SVD">
<code class="descclassname">pyvib.linalg.</code><code class="descname">SVD</code><span class="sig-paren">(</span><em>x</em>, <em>m</em><span class="sig-paren">)</span><a class="headerlink" href="#pyvib.linalg.SVD" title="Permalink to this definition">¶</a></dt>
<dd><p>Produce the singular value decomposition of a signal
Uses the scikit learn.randomized SVD function</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>x</strong> (<em>array 1D float</em>) – The signal to decompose</li>
<li><strong>m</strong> (<em>int</em>) – Number of singular values wanted</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"><ul class="simple">
<li><strong>U</strong> (<em>array 2D float</em>)</li>
<li><strong>sigma</strong> (<em>array 1D float</em>) – The singular values ranging from highest to lowest energy</li>
<li><strong>V</strong> (<em>array 2D float</em>)</li>
</ul>
</p>
</td>
</tr>
</tbody>
</table>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="#pyvib.linalg.get_SVDxi" title="pyvib.linalg.get_SVDxi"><code class="xref py py-func docutils literal notranslate"><span class="pre">get_SVDxi()</span></code></a></p>
</div>
</dd></dl>

<dl class="function">
<dt id="pyvib.linalg.get_SVDxi">
<code class="descclassname">pyvib.linalg.</code><code class="descname">get_SVDxi</code><span class="sig-paren">(</span><em>U</em>, <em>sigma</em>, <em>V</em>, <em>i</em><span class="sig-paren">)</span><a class="headerlink" href="#pyvib.linalg.get_SVDxi" title="Permalink to this definition">¶</a></dt>
<dd><p>Estimate the i’th singular value composition using the diagonal mean sum</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>U</strong> (<em>array 2D float</em>) – </li>
<li><strong>sigma</strong> (<em>array 1D float</em>) – The singular values</li>
<li><strong>V</strong> (<em>array 2D float</em>) – </li>
<li><strong>i</strong> (<em>int</em>) – The i’th singular value to recompose. 0 &lt; i &lt; Sigma.size</li>
</ul>
</td>
</tr>
</tbody>
</table>
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